Data Engineering Manager

Data Engineering Manager

We are looking for an experienced Data Engineering Manager to lead and manage a team of data engineers and analysts working on building scalable data and analytics solutions. This person will participate in architecture and design discussions, own end-to-end solution delivery, stakeholder management, partner with platform engineering, collaborate with other engineering teams, and will guide and mentor data engineers. The ideal candidate will have outstanding communication skills, proven data design and implementation capabilities, strong business acumen, and an innate drive to deliver results. The person in this role will be technically proficient and excel at collaborating with engineers, analysts, and stakeholders. He/she will be a self-starter, comfortable with ambiguity, and will enjoy working in a fast-paced dynamic environment.

In this role, you will manage an engineering team focused on building and delivering scalable data and analytics solutions in our Direct, Supply Chain, and Commercial space. The team will design, implement and integrate new technologies and evolve data and analytics products. You will be contributing to all aspects of data engineering from ingestion, transformation, and consumption in addition to designing and building test-driven development, reusable frameworks, automated workflows, and libraries at scale to support analytics products. You will also participate in architecture and design discussions to process and store high-volume data sets.

This role is part of the North America Data & Analytics Organization and you will work with world-class talent in the field of Data Engineering with a goal of better business insights and driving data-driven decisions across the organization. You'll be working closely with Internal stakeholders, Product Owners, Engineering Leaders, Data Analysts, Big Data Leads, and Engineers. One of our maxims is "Win as a Team" and you will be working in a very collaborative environment and will find success in teamwork, a positive attitude, and hard work.

Requirements include a Bachelor's or Master's degree in Computer Science or related field, 10+ years relevant work experience in the Data Engineering field, 4+ years experience in leading and managing engineering teams, 4+ years experience working with Hadoop and Big Data processing frameworks (Spark, Hive, Nifi, Spark-Streaming, Flink, etc.), 2+ years experience building scalable, real-time and high-performance cloud data lake solutions, strong experience with relational SQL and programming languages such as Python, Scala, or Java, experience with source control tools such as GitHub and related CI/CD processes, experience working with Big Data streaming services such as Kinesis, Kafka, etc., experience working with NoSQL data stores such as HBase, DynamoDB, etc., experience provisioning RESTful API's to enable real-time data consumption, experience working in AWS environment primarily EMR, S3, Kinesis, Redshift, Athena, etc, experience with data warehouses/RDBMS like Snowflake & Teradata, experience with workflow scheduling tools like Airflow, and a strong understanding of algorithms, data structures, data architecture, and technical designs. Has a strong problem solving and analytical approach.